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Techno-economic assessment-guided biofoundry for microbial strain development.

Yu Been Heo1, Sung Cheon Ko1, Jay D Keasling2

  • 1Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea; Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea.

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|December 2, 2025
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Summary
This summary is machine-generated.

We introduce the Experiment Price Index (EPI) to measure the economic efficiency of automated biofoundry workflows. This metric aids in optimizing synthetic biology processes and planning scalable biofoundry operations for sustainable manufacturing.

Keywords:
biofoundryefficiencylab automationstandardizationstrain development

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Area of Science:

  • Biotechnology
  • Synthetic Biology
  • Laboratory Automation

Background:

  • Biofoundries accelerate strain development for sustainable manufacturing using automated Design-Build-Test-Learn (DBTL) workflows.
  • Quantifying the economic efficiency of these automated processes is a significant challenge.

Purpose of the Study:

  • To define and apply a standardized metric, the Experiment Price Index (EPI), for evaluating the economic efficiency of automated biofoundry workflows.
  • To demonstrate the utility of EPI and robot-assisted modules (RAMs) in optimizing synthetic biology workflows and assessing techno-economic factors.

Main Methods:

  • Defined robot-assisted modules (RAMs) as plug-and-play units for workflow construction.
  • Developed and applied the Experiment Price Index (EPI), combining time and cost per sample, to evaluate four strain development workflows.
  • Extended the EPI framework to include techno-economic assessment (TEA), estimating return on investment (ROI) and payback periods.

Main Results:

  • EPI successfully identified workflow bottlenecks and redundancies, enabling optimization.
  • Techno-economic assessments using EPI provided insights into cost-effectiveness and scalability.
  • The developed workflows demonstrated efficient strain development for sustainable manufacturing.

Conclusions:

  • The Experiment Price Index (EPI) is a valuable tool for cost-effective experimental planning and scalable biofoundry deployment.
  • EPI facilitates the optimization of synthetic biology workflows and aids in techno-economic decision-making.
  • EPI serves as a universal metric for evaluating automation efficiency across various biotechnology applications.